Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-09-01 12:04:04	ga_s2am_ard_3-2-1_50KMA_2022-09-01_final.stac-item
2022-09-01 12:04:22	ga_s2am_ard_3-2-1_50KLV_2022-09-01_final.stac-item
2022-09-01 12:06:07	ga_s2am_ard_3-2-1_50JKN_2022-09-01_final.stac-item
2022-09-02 11:31:43	ga_s2am_ard_3-2-1_51LWE_2022-09-02_final.stac-item
2022-09-02 11:33:14	ga_s2am_ard_3-2-1_51KYT_2022-09-02_final.stac-item
2022-09-02 11:34:30	ga_s2am_ard_3-2-1_51KUP_2022-09-02_final.stac-item
2022-09-02 11:34:44	ga_s2am_ard_3-2-1_51JUN_2022-09-02_final.stac-item
2022-09-03 11:06:36	ga_s2am_ard_3-2-1_52HBK_2022-09-03_final.stac-item
2022-09-04 12:15:12	ga_s2am_ard_3-2-1_49JFM_2022-09-04_final.stac-item
2022-09-04 12:15:22	ga_s2am_ard_3-2-1_49JGL_2022-09-04_final.stac-item
2022-09-05 11:41:38	ga_s2am_ard_3-2-1_51LWE_2022-09-05_final.stac-item
2022-09-05 11:43:41	ga_s2am_ard_3-2-1_51KUS_2022-09-05_final.stac-item
2022-09-05 11:44:35	ga_s2am_ard_3-2-1_50KPU_2022-09-05_final.stac-item
2022-09-05 11:44:42	ga_s2am_ard_3-2-1_50JRT_2022-09-05_final.stac-item
2022-09-05 11:44:49	ga_s2am_ard_3-2-1_50JPT_2022-09-05_final.stac-item
2022-09-06 11:14:19	ga_s2am_ard_3-2-1_52JET_2022-09-06_final.stac-item
2022-09-06 11:14:35	ga_s2am_ard_3-2-1_51JZN_2022-09-06_final.stac-item
2022-09-06 11:16:02	ga_s2am_ard_3-2-1_52JBM_2022-09-06_final.stac-item
2022-09-06 11:16:05	ga_s2am_ard_3-2-1_51JYG_2022-09-06_final.stac-item
2022-09-08 11:53:36	ga_s2am_ard_3-2-1_50KNC_2022-09-08_final.stac-item
2022-09-08 11:53:54	ga_s2am_ard_3-2-1_50KMB_2022-09-08_final.stac-item
2022-09-08 11:54:09	ga_s2am_ard_3-2-1_50KMA_2022-09-08_final.stac-item
2022-09-08 11:54:16	ga_s2am_ard_3-2-1_50KPV_2022-09-08_final.stac-item
2022-09-08 11:54:30	ga_s2am_ard_3-2-1_50KPU_2022-09-08_final.stac-item
2022-09-08 11:54:34	ga_s2am_ard_3-2-1_50KNU_2022-09-08_final.stac-item
2022-09-08 11:54:37	ga_s2am_ard_3-2-1_50KMU_2022-09-08_final.stac-item
2022-09-08 11:54:44	ga_s2am_ard_3-2-1_50KLU_2022-09-08_final.stac-item
2022-09-08 11:54:48	ga_s2am_ard_3-2-1_50JNT_2022-09-08_final.stac-item
2022-09-08 11:56:11	ga_s2am_ard_3-2-1_50JKN_2022-09-08_final.stac-item
2022-09-09 11:23:21	ga_s2am_ard_3-2-1_51KYT_2022-09-09_final.stac-item
2022-09-09 11:23:24	ga_s2am_ard_3-2-1_51KXT_2022-09-09_final.stac-item
2022-09-09 11:24:15	ga_s2am_ard_3-2-1_51KZP_2022-09-09_final.stac-item
2022-09-09 11:24:23	ga_s2am_ard_3-2-1_51KXP_2022-09-09_final.stac-item
2022-09-10 10:56:11	ga_s2am_ard_3-2-1_52JFL_2022-09-10_final.stac-item
2022-09-11 12:03:30	ga_s2am_ard_3-2-1_50KNC_2022-09-11_final.stac-item
2022-09-11 12:04:03	ga_s2am_ard_3-2-1_50KMA_2022-09-11_final.stac-item
2022-09-11 12:04:35	ga_s2am_ard_3-2-1_50KLU_2022-09-11_final.stac-item
2022-09-11 12:05:54	ga_s2am_ard_3-2-1_49JGJ_2022-09-11_final.stac-item
2022-09-12 11:31:41	ga_s2am_ard_3-2-1_51LWE_2022-09-12_final.stac-item
2022-09-12 11:33:12	ga_s2am_ard_3-2-1_51KYT_2022-09-12_final.stac-item
2022-09-12 11:33:19	ga_s2am_ard_3-2-1_51KXT_2022-09-12_final.stac-item
2022-09-12 11:33:44	ga_s2am_ard_3-2-1_51KUS_2022-09-12_final.stac-item
2022-09-12 11:34:39	ga_s2am_ard_3-2-1_51JVN_2022-09-12_final.stac-item
2022-09-12 11:34:46	ga_s2am_ard_3-2-1_51JTN_2022-09-12_final.stac-item
2022-09-13 11:04:28	ga_s2am_ard_3-2-1_52JET_2022-09-13_final.stac-item
2022-09-13 11:05:55	ga_s2am_ard_3-2-1_52JEM_2022-09-13_final.stac-item
2022-09-13 11:06:34	ga_s2am_ard_3-2-1_52HBK_2022-09-13_final.stac-item
2022-09-14 12:15:06	ga_s2am_ard_3-2-1_49JGM_2022-09-14_final.stac-item
2022-09-14 12:15:10	ga_s2am_ard_3-2-1_49JFM_2022-09-14_final.stac-item
2022-09-15 11:41:35	ga_s2am_ard_3-2-1_51LWE_2022-09-15_final.stac-item
2022-09-15 11:43:39	ga_s2am_ard_3-2-1_51KUS_2022-09-15_final.stac-item
2022-09-15 11:44:19	ga_s2am_ard_3-2-1_50KPV_2022-09-15_final.stac-item
2022-09-15 11:44:22	ga_s2am_ard_3-2-1_51KUP_2022-09-15_final.stac-item
2022-09-16 11:13:49	ga_s2am_ard_3-2-1_52KBA_2022-09-16_final.stac-item
2022-09-16 11:14:17	ga_s2am_ard_3-2-1_52JET_2022-09-16_final.stac-item
2022-09-16 11:14:18	ga_s2am_ard_3-2-1_51KZP_2022-09-16_final.stac-item
2022-09-16 11:14:33	ga_s2am_ard_3-2-1_51JZN_2022-09-16_final.stac-item
2022-09-16 11:16:29	ga_s2am_ard_3-2-1_52HBK_2022-09-16_final.stac-item
2022-09-18 11:53:33	ga_s2am_ard_3-2-1_50KNC_2022-09-18_final.stac-item
2022-09-18 11:54:13	ga_s2am_ard_3-2-1_50KPV_2022-09-18_final.stac-item
2022-09-18 11:54:31	ga_s2am_ard_3-2-1_50KNU_2022-09-18_final.stac-item
2022-09-18 11:54:35	ga_s2am_ard_3-2-1_50KMU_2022-09-18_final.stac-item
2022-09-18 11:54:46	ga_s2am_ard_3-2-1_50JNT_2022-09-18_final.stac-item
2022-09-19 11:23:22	ga_s2am_ard_3-2-1_51KXT_2022-09-19_final.stac-item
2022-09-19 11:24:20	ga_s2am_ard_3-2-1_51KXP_2022-09-19_final.stac-item
2022-09-20 10:55:57	ga_s2am_ard_3-2-1_52JEM_2022-09-20_final.stac-item
2022-09-21 12:03:27	ga_s2am_ard_3-2-1_50KNC_2022-09-21_final.stac-item
2022-09-21 12:03:45	ga_s2am_ard_3-2-1_50KMB_2022-09-21_final.stac-item
2022-09-21 12:03:59	ga_s2am_ard_3-2-1_50KMA_2022-09-21_final.stac-item
2022-09-21 12:04:18	ga_s2am_ard_3-2-1_50KLV_2022-09-21_final.stac-item
2022-09-21 12:04:29	ga_s2am_ard_3-2-1_50KMU_2022-09-21_final.stac-item
2022-09-21 12:04:40	ga_s2am_ard_3-2-1_50KLU_2022-09-21_final.stac-item
2022-09-21 12:04:41	ga_s2am_ard_3-2-1_50JKT_2022-09-21_final.stac-item
2022-09-21 12:05:04	ga_s2am_ard_3-2-1_50JKS_2022-09-21_final.stac-item
2022-09-21 12:05:08	ga_s2am_ard_3-2-1_49JGM_2022-09-21_final.stac-item
2022-09-21 12:05:19	ga_s2am_ard_3-2-1_50JKR_2022-09-21_final.stac-item
2022-09-21 12:05:51	ga_s2am_ard_3-2-1_49JGJ_2022-09-21_final.stac-item
2022-09-22 11:31:38	ga_s2am_ard_3-2-1_51LWE_2022-09-22_final.stac-item
2022-09-22 11:33:23	ga_s2am_ard_3-2-1_51KVT_2022-09-22_final.stac-item
2022-09-22 11:34:32	ga_s2am_ard_3-2-1_51JWN_2022-09-22_final.stac-item
2022-09-23 11:04:25	ga_s2am_ard_3-2-1_52JET_2022-09-23_final.stac-item
2022-09-23 11:05:52	ga_s2am_ard_3-2-1_52JEM_2022-09-23_final.stac-item
2022-09-24 12:15:03	ga_s2am_ard_3-2-1_49JGM_2022-09-24_final.stac-item
2022-09-24 12:15:07	ga_s2am_ard_3-2-1_49JFM_2022-09-24_final.stac-item
2022-09-24 12:15:17	ga_s2am_ard_3-2-1_49JGL_2022-09-24_final.stac-item
2022-09-25 11:44:20	ga_s2am_ard_3-2-1_51KUP_2022-09-25_final.stac-item
2022-09-25 11:44:23	ga_s2am_ard_3-2-1_50KRU_2022-09-25_final.stac-item
2022-09-26 11:14:15	ga_s2am_ard_3-2-1_52JET_2022-09-26_final.stac-item
2022-09-26 11:14:16	ga_s2am_ard_3-2-1_51KZP_2022-09-26_final.stac-item
2022-09-26 11:16:01	ga_s2am_ard_3-2-1_51JYG_2022-09-26_final.stac-item
2022-09-28 11:53:50	ga_s2am_ard_3-2-1_50KMB_2022-09-28_final.stac-item
2022-09-28 11:54:05	ga_s2am_ard_3-2-1_50KMA_2022-09-28_final.stac-item
2022-09-28 11:54:40	ga_s2am_ard_3-2-1_50KLU_2022-09-28_final.stac-item
2022-09-28 11:54:44	ga_s2am_ard_3-2-1_50JNT_2022-09-28_final.stac-item
2022-09-28 11:56:07	ga_s2am_ard_3-2-1_50JKN_2022-09-28_final.stac-item
2022-09-29 11:23:17	ga_s2am_ard_3-2-1_51KYT_2022-09-29_final.stac-item
2022-09-29 11:23:21	ga_s2am_ard_3-2-1_51KXT_2022-09-29_final.stac-item
2022-09-29 11:23:57	ga_s2am_ard_3-2-1_52KBV_2022-09-29_final.stac-item
2022-09-29 11:24:11	ga_s2am_ard_3-2-1_51KZP_2022-09-29_final.stac-item
2022-09-30 10:55:56	ga_s2am_ard_3-2-1_52JEM_2022-09-30_final.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years